| Learning two layer rectified neural networks in polynomial time A Bakshi, R Jayaram, DP Woodruff Conference on Learning Theory, 195-268, 2019 | 87 | 2019 |
| File systems fated for senescence? nonsense, says science! A Conway, A Bakshi, Y Jiao, W Jannen, Y Zhan, J Yuan, MA Bender, ... 15th USENIX Conference on File and Storage Technologies (FAST 17), 45-58, 2017 | 87 | 2017 |
| Robustly learning mixtures of k arbitrary Gaussians A Bakshi, I Diakonikolas, H Jia, DM Kane, PK Kothari, SS Vempala Proceedings of the 54th Annual ACM SIGACT Symposium on Theory of Computing …, 2022 | 75 | 2022 |
| Robust linear regression: Optimal rates in polynomial time A Bakshi, A Prasad Proceedings of the 53rd Annual ACM SIGACT Symposium on Theory of Computing …, 2021 | 68 | 2021 |
| List-decodable subspace recovery: Dimension independent error in polynomial time A Bakshi, PK Kothari Proceedings of the 2021 ACM-SIAM Symposium on Discrete Algorithms (SODA …, 2021 | 51* | 2021 |
| Outlier-robust clustering of non-spherical mixtures A Bakshi, P Kothari arXiv preprint arXiv:2005.02970, 2020 | 44 | 2020 |
| Sublinear time low-rank approximation of distance matrices A Bakshi, DP Woodruff arXiv preprint arXiv:1809.06986, 2018 | 39* | 2018 |
| Outlier-robust clustering of gaussians and other non-spherical mixtures A Bakshi, I Diakonikolas, SB Hopkins, D Kane, S Karmalkar, PK Kothari 2020 ieee 61st annual symposium on foundations of computer science (focs …, 2020 | 33 | 2020 |
| Learning quantum Hamiltonians at any temperature in polynomial time A Bakshi, A Liu, A Moitra, E Tang Proceedings of the 56th Annual ACM Symposium on Theory of Computing, 1470-1477, 2024 | 27 | 2024 |
| Low-rank approximation with 1/𝜖1/3 matrix-vector products A Bakshi, KL Clarkson, DP Woodruff Proceedings of the 54th Annual ACM SIGACT Symposium on Theory of Computing …, 2022 | 25 | 2022 |
| Robust and sample optimal algorithms for PSD low rank approximation A Bakshi, N Chepurko, DP Woodruff 2020 IEEE 61st Annual Symposium on Foundations of Computer Science (FOCS …, 2020 | 22 | 2020 |
| Testing positive semi-definiteness via random submatrices A Bakshi, N Chepurko, R Jayaram 2020 IEEE 61st Annual Symposium on Foundations of Computer Science (FOCS …, 2020 | 21 | 2020 |
| High-temperature Gibbs states are unentangled and efficiently preparable A Bakshi, A Liu, A Moitra, E Tang arXiv preprint arXiv:2403.16850, 2024 | 16 | 2024 |
| An improved classical singular value transformation for quantum machine learning A Bakshi, E Tang Proceedings of the 2024 Annual ACM-SIAM Symposium on Discrete Algorithms …, 2024 | 16 | 2024 |
| A new approach to learning linear dynamical systems A Bakshi, A Liu, A Moitra, M Yau Proceedings of the 55th Annual ACM Symposium on Theory of Computing, 335-348, 2023 | 14 | 2023 |
| A novel feature selection and extraction technique for classification K Goel, R Vohra, A Bakshi 2014 14th International Conference on Frontiers in Handwriting Recognition …, 2014 | 13 | 2014 |
| Krylov methods are (nearly) optimal for low-rank approximation A Bakshi, S Narayanan 2023 IEEE 64th Annual Symposium on Foundations of Computer Science (FOCS …, 2023 | 11 | 2023 |
| Structure learning of Hamiltonians from real-time evolution A Bakshi, A Liu, A Moitra, E Tang arXiv preprint arXiv:2405.00082, 2024 | 10* | 2024 |
| Learning a Latent Simplex in Input-Sparsity Time A Bakshi, C Bhattacharyya, R Kannan, DP Woodruff, S Zhou arXiv preprint arXiv:2105.08005, 2021 | 10 | 2021 |
| Chance constraint based multi-objective vendor selection using NSGAII R Aggarwal, A Bakshi Procedia Computer Science 48, 699-705, 2015 | 10 | 2015 |
